Linguistically Invariant Inductive Logic

1970 ◽  
pp. 33-55
Author(s):  
Ian Hacking
Keyword(s):  
Inductive Logic

Carnap's "On Inductive Logic"

1946 ◽  
Vol 13 (4) ◽  
pp. 339-342 ◽  
Author(s):  
C. West Churchman
Keyword(s):  
Inductive Logic

Hilpinen's Rules of Acceptance and Inductive Logic

1971 ◽  
Vol 38 (2) ◽  
pp. 293-302 ◽  
Author(s):  
Alex C. Michalos
Keyword(s):  
Inductive Logic

ILPNET repositories on WWW: Inductive Logic Programming systems, datasets and bibliography

1996 ◽  
Vol 9 (4) ◽  
pp. 157-206 ◽  
Author(s):  
Nada Lavrač ◽  
Irene Weber ◽  
Darko Zupanič ◽  
Dimitar Kazakov ◽  
Olga Štěpánková ◽  
...  
Keyword(s):  
Logic Programming ◽  
Inductive Logic Programming ◽  
Inductive Logic ◽  
Programming Systems

scholarly journals A First Step towards Learning which uORFs Regulate Gene Expression

2006 ◽  
Vol 3 (2) ◽  
pp. 109-122 ◽  
Author(s):  
◽  
Christopher H. Bryant ◽  
Graham J.L. Kemp ◽  
Marija Cvijovic
Keyword(s):  
Gene Expression ◽  
Inductive Logic ◽  
Preliminary Evidence ◽  
Open Reading Frames ◽  
Yeast Saccharomyces Cerevisiae ◽  
Regulate Gene Expression ◽  
Integrative System ◽  
Upstream Open Reading Frames ◽  
Reading Frames ◽  
Regulate Gene

Summary We have taken a first step towards learning which upstream Open Reading Frames (uORFs) regulate gene expression (i.e., which uORFs are functional) in the yeast Saccharomyces cerevisiae. We do this by integrating data from several resources and combining a bioinformatics tool, ORF Finder, with a machine learning technique, inductive logic programming (ILP). Here, we report the challenge of using ILP as part of this integrative system, in order to automatically generate a model that identifies functional uORFs. Our method makes searching for novel functional uORFs more efficient than random sampling. An attempt has been made to predict novel functional uORFs using our method. Some preliminary evidence that our model may be biologically meaningful is presented.

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